DocumentCode
1563505
Title
A Modified Particle Swarm Optimization Algorithm
Author
Shuhua, Wen ; Xueliang, Zhang ; Hainan, Li ; Shuyang, Liu ; Jiaying, Wang
Author_Institution
Taiyuan Univ. of Sci. & Technol.
Volume
1
fYear
2005
Firstpage
318
Lastpage
321
Abstract
A modified particle swarm optimization (MPSO) algorithm is presented based on the variance of the population´s fitness. During computing, the inertia weight of MPSO is determined adaptively and randomly according to the variance of the populations fitness. And the ability of , particle swarm optimization algorithm (PSO) to break away from the local optimum is greatly improved. The simulating results show that this algorithm not only has great advantage of convergence property over standard simple PSO, but also can avoid the premature convergence problem effectively
Keywords
particle swarm optimisation; convergence property; modified particle swarm optimization; populations fitness; Birds; Computational modeling; Convergence; Educational institutions; Evolutionary computation; Genetic algorithms; Genetic mutations; Marine animals; Particle swarm optimization; Particle tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9422-4
Type
conf
DOI
10.1109/ICNNB.2005.1614623
Filename
1614623
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